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- W1696166066 abstract "We consider the following problem: There is a set of items (e.g., movies) and a group of agents (e.g., passengers on a plane); each agent has some intrinsic utility for each of the items. Our goal is to pick a set of K items that maximize the total derived utility of all the agents (i.e., in our example we are to pick K movies that we put on the plane's entertainment system). However, the actual utility that an agent derives from a given item is only a fraction of its intrinsic one, and this fraction depends on how the agent ranks the item among the chosen, available, ones. We provide a formal specification of the model and provide concrete examples and settings where it is applicable. We show that the problem is hard in general, but we show a number of tractability results for its natural special cases." @default.
- W1696166066 created "2016-06-24" @default.
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- W1696166066 date "2015-02-18" @default.
- W1696166066 modified "2023-10-16" @default.
- W1696166066 title "Finding a Collective Set of Items: From Proportional Multirepresentation to Group Recommendation" @default.
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- W1696166066 doi "https://doi.org/10.1609/aaai.v29i1.9431" @default.
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